The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on...The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.展开更多
Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in...Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in this paper.The method implicitly describes structural material in- terfaces by the vector level set and achieves the optimal shape and topology through the continuous evolution of the material interfaces in the structure.In order to increase computational efficiency for a fast convergence,an appropriate nonlinear speed mapping is established in the tangential space of the active constraints.Meanwhile,in order to overcome the numerical instability of general topology opti- mization problems,the regularization with the mean curvature flow is utilized to maintain the interface smoothness during the optimization process.The numerical examples demonstrate that the approach possesses a good flexibility in handling topological changes and gives an interface representation in a high fidelity,compared with other methods based on explicit boundary variations in the literature.展开更多
当微电网负荷功率发生波动时,储能系统能够通过控制逆变器维持系统电压频率稳定。储能逆变器通常采用PI双闭环控制策略,但是由于PI控制存在滞后性,导致系统动态响应速度慢。为此,提出一种考虑Lyapunov稳定约束的有限集模型预测控制(fini...当微电网负荷功率发生波动时,储能系统能够通过控制逆变器维持系统电压频率稳定。储能逆变器通常采用PI双闭环控制策略,但是由于PI控制存在滞后性,导致系统动态响应速度慢。为此,提出一种考虑Lyapunov稳定约束的有限集模型预测控制(finite control set-model predictive control,FCS-MPC)策略。首先,通过Lyapunov稳定约束实现对主控制目标电容电压的稳定控制,再根据电容电压总谐波失真约束项的轻重设置权重系数;然后,通过使目标函数最小实现协同控制,解决传统FCS-MPC目标函数耦合导致系统不稳定以及权重系数难以整定的问题,将改进后的FCS-MPC方法和下垂控制相结合控制储能逆变器;最后,在MATLAB和RT-LAB平台上进行仿真验证。仿真结果表明:与传统控制策略相比,改进后的FCS-MPC方法可以提高系统动态响应速度,实现多目标协同控制并且对权重系数有很好的鲁棒性。展开更多
为了准确地描述新能源输出功率的波动性和随机性对多能互补微网系统运行的影响,提出了基于数据驱动的多能微网鲁棒优化方法。首先,在传统区间集合的基础上对新能源出力的不确定参数进行多面体集合建模,然后利用具有时空相关性的新能源...为了准确地描述新能源输出功率的波动性和随机性对多能互补微网系统运行的影响,提出了基于数据驱动的多能微网鲁棒优化方法。首先,在传统区间集合的基础上对新能源出力的不确定参数进行多面体集合建模,然后利用具有时空相关性的新能源出力历史数据建立椭球不确定集合,通过连接高维椭球顶点,建立了数据驱动的凸包多面体集合,接着通过放缩凸包集合更好地对不确定参数进行包络。进一步建立了基于数据驱动的多能互补微网鲁棒优化模型,并采用列与约束生成算法(Column and constraint generation,C&CG)对该模型进行求解。最后通过算例进行仿真对比,结果表明,基于数据驱动的多能互补微网鲁棒优化方法可以减少保守性,提高优化结果鲁棒性,证明了所提方法的有效性。展开更多
To determine the reasonable resource dependent relations between activities for the purpose of exactly computing the total floats and the free floats of activities, correctly identifying critical activities and critic...To determine the reasonable resource dependent relations between activities for the purpose of exactly computing the total floats and the free floats of activities, correctly identifying critical activities and critical sequences in a project schedule with variable resource constraints, the concept of the minimal feasible set （MFS） is proposed and the properties of MFS are discussed. The methods to identify optimal MFSs and resource links are then studied. Furthermore, MFS is generalized to the situation that the preconditions of MFS are not satisfied. Contrastive results show that in establishing resource links and resolving floats, MFS is at least not inferior to other methods in all cases and is superior in most situations.展开更多
Without prior knowledge,the steering vector estimation error of the desired signal will deteriorate the beamforming performance to some extent.To solve this problem,a space-time blind wideband beamforming algorithm ba...Without prior knowledge,the steering vector estimation error of the desired signal will deteriorate the beamforming performance to some extent.To solve this problem,a space-time blind wideband beamforming algorithm based on the uncertainty set is proposed.First of all,based on the space-time filtering model,the spherical constraint set is designed according to the uncertainty of the estimation error of the space-time steering vector.Then,the method of wideband beamforming under multiconstraints in the frequency domain is derived,and the calculation of parameters of steering vector estimation error and loading factor are given in detail.Finally,a blind broadband beamforming algorithm combined with the CAB algorithm is proposed.The improvement of the output signal-to-noise ratio is quantitatively analyzed by computer simulation to verify the correctness and robustness of the algorithm.展开更多
Posterior constraint optimal selection techniques (COSTs) are developed for nonnegative linear programming problems (NNLPs), and a geometric interpretation is provided. The posterior approach is used in both a dynamic...Posterior constraint optimal selection techniques (COSTs) are developed for nonnegative linear programming problems (NNLPs), and a geometric interpretation is provided. The posterior approach is used in both a dynamic and non-dynamic active-set framework. The computational performance of these methods is compared with the CPLEX standard linear programming algorithms, with two most-violated constraint approaches, and with previously developed COST algorithms for large-scale problems.展开更多
We describe a new active-set, cutting-plane Constraint Optimal Selection Technique (COST) for solving general linear programming problems. We describe strategies to bound the initial problem and simultaneously add mul...We describe a new active-set, cutting-plane Constraint Optimal Selection Technique (COST) for solving general linear programming problems. We describe strategies to bound the initial problem and simultaneously add multiple constraints. We give an interpretation of the new COST’s selection rule, which considers both the depth of constraints as well as their angles from the objective function. We provide computational comparisons of the COST with existing linear programming algorithms, including other COSTs in the literature, for some large-scale problems. Finally, we discuss conclusions and future research.展开更多
基金supported by the National Natural Science Foundation of China(62176218,62176027)the Fundamental Research Funds for the Central Universities(XDJK2020TY003)the Funds for Chongqing Talent Plan(cstc2024ycjh-bgzxm0082)。
文摘The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.
基金The project supported by the National Natural Science Foundation of China (59805001,10332010) and Key Science and Technology Research Project of Ministry of Education of China (No.104060)
文摘Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in this paper.The method implicitly describes structural material in- terfaces by the vector level set and achieves the optimal shape and topology through the continuous evolution of the material interfaces in the structure.In order to increase computational efficiency for a fast convergence,an appropriate nonlinear speed mapping is established in the tangential space of the active constraints.Meanwhile,in order to overcome the numerical instability of general topology opti- mization problems,the regularization with the mean curvature flow is utilized to maintain the interface smoothness during the optimization process.The numerical examples demonstrate that the approach possesses a good flexibility in handling topological changes and gives an interface representation in a high fidelity,compared with other methods based on explicit boundary variations in the literature.
文摘当微电网负荷功率发生波动时,储能系统能够通过控制逆变器维持系统电压频率稳定。储能逆变器通常采用PI双闭环控制策略,但是由于PI控制存在滞后性,导致系统动态响应速度慢。为此,提出一种考虑Lyapunov稳定约束的有限集模型预测控制(finite control set-model predictive control,FCS-MPC)策略。首先,通过Lyapunov稳定约束实现对主控制目标电容电压的稳定控制,再根据电容电压总谐波失真约束项的轻重设置权重系数;然后,通过使目标函数最小实现协同控制,解决传统FCS-MPC目标函数耦合导致系统不稳定以及权重系数难以整定的问题,将改进后的FCS-MPC方法和下垂控制相结合控制储能逆变器;最后,在MATLAB和RT-LAB平台上进行仿真验证。仿真结果表明:与传统控制策略相比,改进后的FCS-MPC方法可以提高系统动态响应速度,实现多目标协同控制并且对权重系数有很好的鲁棒性。
文摘为了准确地描述新能源输出功率的波动性和随机性对多能互补微网系统运行的影响,提出了基于数据驱动的多能微网鲁棒优化方法。首先,在传统区间集合的基础上对新能源出力的不确定参数进行多面体集合建模,然后利用具有时空相关性的新能源出力历史数据建立椭球不确定集合,通过连接高维椭球顶点,建立了数据驱动的凸包多面体集合,接着通过放缩凸包集合更好地对不确定参数进行包络。进一步建立了基于数据驱动的多能互补微网鲁棒优化模型,并采用列与约束生成算法(Column and constraint generation,C&CG)对该模型进行求解。最后通过算例进行仿真对比,结果表明,基于数据驱动的多能互补微网鲁棒优化方法可以减少保守性,提高优化结果鲁棒性,证明了所提方法的有效性。
基金supported partly by the Postdoctoral Science Foundation of China(2007042-0922)the Program of Educational Commission of Guangxi Zhuang Minority Autonomous Region(200712LX128)the Scientific Research Foundation of Guangxi University for Nationalities for Talent Introduction(200702YZ01).
文摘To determine the reasonable resource dependent relations between activities for the purpose of exactly computing the total floats and the free floats of activities, correctly identifying critical activities and critical sequences in a project schedule with variable resource constraints, the concept of the minimal feasible set （MFS） is proposed and the properties of MFS are discussed. The methods to identify optimal MFSs and resource links are then studied. Furthermore, MFS is generalized to the situation that the preconditions of MFS are not satisfied. Contrastive results show that in establishing resource links and resolving floats, MFS is at least not inferior to other methods in all cases and is superior in most situations.
文摘Without prior knowledge,the steering vector estimation error of the desired signal will deteriorate the beamforming performance to some extent.To solve this problem,a space-time blind wideband beamforming algorithm based on the uncertainty set is proposed.First of all,based on the space-time filtering model,the spherical constraint set is designed according to the uncertainty of the estimation error of the space-time steering vector.Then,the method of wideband beamforming under multiconstraints in the frequency domain is derived,and the calculation of parameters of steering vector estimation error and loading factor are given in detail.Finally,a blind broadband beamforming algorithm combined with the CAB algorithm is proposed.The improvement of the output signal-to-noise ratio is quantitatively analyzed by computer simulation to verify the correctness and robustness of the algorithm.
文摘Posterior constraint optimal selection techniques (COSTs) are developed for nonnegative linear programming problems (NNLPs), and a geometric interpretation is provided. The posterior approach is used in both a dynamic and non-dynamic active-set framework. The computational performance of these methods is compared with the CPLEX standard linear programming algorithms, with two most-violated constraint approaches, and with previously developed COST algorithms for large-scale problems.
文摘We describe a new active-set, cutting-plane Constraint Optimal Selection Technique (COST) for solving general linear programming problems. We describe strategies to bound the initial problem and simultaneously add multiple constraints. We give an interpretation of the new COST’s selection rule, which considers both the depth of constraints as well as their angles from the objective function. We provide computational comparisons of the COST with existing linear programming algorithms, including other COSTs in the literature, for some large-scale problems. Finally, we discuss conclusions and future research.
